title: Phase and amplitude imaging from noisy images by Kalman filtering.
abstract: We propose and demonstrate a computational method for complex-field imaging from many noisy intensity images with varying defocus, using an extended complex Kalman filter. The technique offers dynamic smoothing of noisy measurements and is recursive rather than iterative, so is suitable for adaptive measurements. The Kalman filter provides near-optimal results in very low-light situations and may be adapted to propagation through turbulent, scattering, or nonlinear media.
authors.affiliation: Department of Electrical Engineering and Computer Science,Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA. lwaller@alum.mit.edu
authors.forename: Laura
authors.initials: L
authors.lastname: Waller
authors.forename: Mankei
authors.initials: M
authors.lastname: Tsang
authors.forename: Sameera
authors.initials: S
authors.lastname: Ponda
authors.forename: Se Young
authors.initials: SY
authors.lastname: Yang
authors.forename: George
authors.initials: G
authors.lastname: Barbastathis
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted